Caltech101
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Caltech101 Base and New Classes | Base Accuracy98.97 | 72 | |
| Image Classification | Caltech101 | Base Accuracy99.3 | 68 | |
| Image Classification | Caltech101 few-shot | Accuracy95.1 | 32 | |
| Multi-view Clustering | Caltech101 20 | ACC76.81 | 30 | |
| Fine-grained classification | Caltech101 (base classes) | Accuracy98.23 | 27 | |
| Image Classification | Caltech101 MDCII Order-II | Transfer Accuracy95.1 | 15 | |
| Fine-grained classification | Caltech101 (novel classes) | MCE0.39 | 15 | |
| Few-shot Image Classification | Caltech101 (test) | Accuracy (1-shot)94.17 | 15 | |
| Image Classification | Caltech101 (Novel) | Top-1 Acc94.67 | 15 | |
| Image Classification | Caltech101 MDCII Order-I | Transfer Accuracy74.5 | 13 | |
| Image Classification | N-Caltech101 (test) | Accuracy81.73 | 13 | |
| Fine-grained classification | Caltech101 fine-grained (base) | MCE0.24 | 12 | |
| Image Classification | Caltech101 New classes | Accuracy94.93 | 12 | |
| Image Classification | Caltech101 Base classes | Accuracy99.23 | 12 | |
| Image Classification | CalTech101 zero-shot | Clean Accuracy93.6 | 11 | |
| Semi-supervised classification | Caltech101 7 | Accuracy97.5 | 10 | |
| Image Classification | Caltech101 VTAB natural (test) | Accuracy98.56 | 9 | |
| Clustering | CALTECH101-7 | AMI0.6592 | 9 | |
| Image Classification | Caltech101 Pathological Non-IID (test) | Accuracy97.02 | 9 | |
| Event-based Classification | N-Caltech101 (test) | GFLOPs0.7 | 9 | |
| Ownership Verification | Caltech101 (test) | Base Score98.2 | 7 | |
| Image Anonymization Evaluation | Caltech101 | CLIP Score30.94 | 7 | |
| Classification | Caltech101 20 | Accuracy92.48 | 7 | |
| Clustering | Caltech101 20 (test) | Accuracy45.12 | 7 | |
| Few-shot Classification | Caltech101 16-shot (test) | Accuracy (Sym 0.125)92.07 | 5 |
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